The present invention relates sonar and radar, and, more particularly, to methods of rapid and accurate mapping of the characteristics of nearby scatterers for array sonar and radar.
It is a problem in known array sonar systems to rapidly obtain an accurate map of the location, strength and movement of primary scatterers in the media immediately surrounding a sonar array. This is important where there are multiple sources of interest, e.g. determining ocean surface and volume backscatter characteristics, estimation of fish population, robotic vehicle sensors, target identification, and torpedo terminal homing. In the latter cases, the multiple sources are from a single target and may be used to establish vital charateristics of the target: class, position, orientation and motion. Critical requirements in many of these situations are the ability to perform rapid computations and the ability to survey near regions in all directions prior to ones further away.
Several features of conventional sonars limit the accuracy or ability of these systems to solve this problem. These features include the general practice for the simplest to the most sophisticated sonar receivers of partitioning the receiver into a spatial and a temporal part. This practice is based on Middleton D. and Groginsky. H. L., "Detection of Random Acoustic Signals by Receivers with Distributed Elements: Optimum Receiver Structures for Normal Signal and Noise Fields", Journal Acoustic Society of America 38, 727 (1965) and Straddling C. S. and Baggeroer A. B. "Joint Active and Passive Sonar Signal Processing using Arrays", Naval Research and Development Center TP 121, December 1968. The first part of the sonar receiver processor depends only on array properties and involves spatial processing or beamforming. Samples of the received signal are multiplied by a weight and delayed before combining in order to provide different sensitivities to different angular directions. Usually this sensitivity is maximized for a given direction. The second part of the processor depends on statistical properties of the signal and external and internal noise, e.g. matched filtering. These approaches encounter difficulties when applied to the specific problem of close, fast moving multiple scatterers.
Several problems arise directly from this use of receiver beamforming. (1) A major source of performance degradation with beams is caused by the existence of side lobes or directions having sensitivity peaks other than the desired main lobe peak. A source in a side lobe direction, a direction substantially different from that of the main lobe, cannot be distinguished in direction from a weaker source in the main lobe direction. Reduction of side lobe sensitivity magnitude may be accomplished at the expense of an undesirable degradation in angular resolution of the main lobe. Widlely spread scatterers may not be accurately located due to sidelobes. Adaptive beamforming, including recent developments in high resolution eigen beamforming (see Schmidt R., "Multiple Emitter Location and Signal Parameter Estimation", Proc. RADC Spectral Estimation Workshop, Rome N.Y. 1979, p243-258 and Wax M and Kailath T, "Extending the Thresholds of the Eigenstructure Methods", Proc. International Conference on Acoustics, Speech and Signal Processing, (1985) enable the determination of accurate direction for discrete far scatterers and would not be expected to perform well with close, fast moving sources or scatterers. (See items (3) and (4) below.)
(2) The desire for wide or omnidirectional coverage, with narrow beams for directional information, means that the beam must be rotated by mechanical or electronic means through a wide angle. The rotation must be sufficiently slow so that energy from the furthest distance to be scanned has time to return to the array before the beam is moved to the next angular direction. An approaching object has time to approach from a given direction while the beam is scanning other directions. The cost of simultaneously forming a large number of beams for substantial angular coverage is normally too great for practical consideration. Close, fast moving multiple scatterers, as might arise in torpedo terminal homing, do not permit time for scanning. Simultaneous forming of multiple beams would generally require more equipment than would be economic or physically reasonable.
(3) Conventional beamforming assumes that the sources are at a sufficient distance that the waves striking the array have plane wave fronts. This determines the phase delays to be incorporated at each receiving element so that signals from the elements will add for waves coming from a specific direction. Near sources will not generate plane wave fronts at the array. Near may be many kilometers for surveillance arrays spreading over tens of kilometers.
(4) Partitioning a sonar receiver into spatial and temporal parts is optimal only for stationary processes. Scatterers with speeds having high transverse components at short range will not meet this criteria and will present difficulties for a scheme that scans by pie slices.
(5) A source of scatterers falling between two adjacent beams is not distinguishable from two sources, one for each beam direction.
(6) Environmental conditions are not normally accounted for during beamforming.
(7) The entire computation is performed at the time of beamforming. Prior computation is not normally used to reduce real time computational load or to permit more complex computations. In addition spectral methods such as Fast Fourier transforms cannot be used when the array elements are not evenly spaced.
The receiver beamformers described above are followed by a temporal processor that for an active sonar involves correlations with matched filters having a range of time delays for range estimation and a range of Doppler frequencies for transverse speed estimation; see Van Trees H. L. "Detection, Estimation and Modulation Theory, Pt III, Radar-Sonar Signal Processing and Gaussian Signals in Noise", Wiley and Sons, 1971. Variations in Doppler frequency across the array for near sources cannot be taken into account because beamforming was previously performed. Similarly variations in range across the array represent error for near sources. Also detection performance is degraded for near sources because of the variation of signal across the array not accurately accounted for by beamforming.